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authorJarrod Millman <jarrod.millman@gmail.com>2020-12-03 07:07:24 -0800
committerGitHub <noreply@github.com>2020-12-03 07:07:24 -0800
commit7af4df0e9251adcec081caec7ed6d8384af5be2c (patch)
tree45afe9f184108801b223e98456c9363b55e37950 /examples
parent0ead17fb18334040b84dd614d1f12d6d3fa9e130 (diff)
downloadnetworkx-7af4df0e9251adcec081caec7ed6d8384af5be2c.tar.gz
Add plot for rcm example (#4411)
Diffstat (limited to 'examples')
-rw-r--r--examples/algorithms/plot_rcm.py14
1 files changed, 10 insertions, 4 deletions
diff --git a/examples/algorithms/plot_rcm.py b/examples/algorithms/plot_rcm.py
index 8ea926e7..61b49bb7 100644
--- a/examples/algorithms/plot_rcm.py
+++ b/examples/algorithms/plot_rcm.py
@@ -1,18 +1,21 @@
"""
-===
-Rcm
-===
+======================
+Reverse Cuthill--McKee
+======================
Cuthill-McKee ordering of matrices
-The reverse Cuthill-McKee algorithm gives a sparse matrix ordering that
+The reverse Cuthill--McKee algorithm gives a sparse matrix ordering that
reduces the matrix bandwidth.
"""
import networkx as nx
from networkx.utils import reverse_cuthill_mckee_ordering
+import matplotlib.pyplot as plt
+import seaborn as sns
import numpy as np
+
# build low-bandwidth numpy matrix
G = nx.grid_2d_graph(3, 3)
rcm = list(reverse_cuthill_mckee_ordering(G))
@@ -33,3 +36,6 @@ x, y = np.nonzero(B)
# print(f"upper bandwidth: {(x - y).max()}")
print(f"bandwidth: {(y - x).max() + (x - y).max() + 1}")
print(B)
+
+sns.heatmap(B.todense(), cbar=False, square=True, linewidths=0.5, annot=True)
+plt.show()